This work addresses an autonomous underwater vehicle (AUV) for applying nonlinear control which is capable of disturbance rejection via intelligent estimation of uncertainties. Adaptive radial basis function neural network (RBF NN) controller is proposed to approximate unknown nonlinear dynamics. The problem of designing an adaptive RBF NN controller was augmented with sliding mode robust term ...

This work presents two simple and robust techniques based on time delay estimation for the respective control and synchronization of chaos systems. First, one of these techniques is applied to the control of a chaotic Lorenz system with both matched and mis-matched uncertainties. The nonlinearities in the Lorenz system is cancelled by time delay estimation and desired error dynamics is inserted...

This paper develops an intelligent robust control algorithm for a class of uncertain nonlinear multivariable systems by using a recurrent-cerebellar-modelarticulation-controller (RCMAC) and sliding mode technology. The proposed control algorithm consists of an adaptive RCMAC and a robust controller. The adaptive RCMAC is a main tracking controller utilized to mimic an ideal sliding mode control...

In this paper, a comparative study of adaptive vibration control approaches is presented for the system identification for microelectro-mechanical systems (MEMS) z-axis gyroscope. Two adaptive methodologies such as adaptive controller and adaptive sliding mode controller are developed and compared in the aspect of algorithm derivation and Lyapunov stability analysis. The proposed adaptive contr...

An adaptive-fuzzy-identification-based sliding-mode control (AFISMC) design method is proposed to control an Linear Ultrasonic Motor (LUSM). Since the dynamic characteristic of the LUSM is difficult to obtain and the motor parameters are time varying, the AFISMC system is derived to automatically adjust the fuzzy rules without using any plant model of the LUSM. In the proposed AFISMC design met...

In this paper, we describe a method of stability analysis for a GA-Based reference adaptive fuzzy sliding model controller for the handling of these problems for a nonlinear system. Firstly, an uncertain and nonlinear plant for the tracking of a reference trajectory is well approximated and described via a fuzzy model involving fuzzy logic control rules. Then, the initial values of the conseque...

This paper presents a novel Adaptive Fuzzy Sliding Mode Controller (AFSMC) for a model-scaled unmanned helicopter as real nonlinear plant. First, in order to efficient control law design, the nonlinear model of the helicopter is reformulated as an affine nonlinear system. To do this aim, a Dynamic Inverter (DI) is introduced as a bijective function. The proposed DI is used to interconnect the h...

Control robustness is study for uncertain nonlinear systems transformed in semi strict feedback systems. An adaptive backstepping sliding mode control and an adaptive backstepping control robustness is considered. Robustness is studied when the unknown parameter are constants and varied. The simulation results prove that the sliding mode control is more robust than the backstepping control to t...

Abstract: This paper presents a robust non-linear hybrid controller based on Type-2 fuzzy and sliding mode control strategy for VSC-HVDC transmission link, which inherits the benefits of these two methods. The interval Type-2 fuzzy (IT2FSMC) is used to handle the uncertainties to enhance the real time performance. The sliding mode control combines with the fuzzy system to compensate the influen...